Content adaptation techniques for localization of content presentation

ABSTRACT

Techniques for localization of a content presentation in an information processing system are provided. In one example, a method adapts translated content to accommodate an original content design structure (e.g., wireframe) when such translated content is inconsistent with the original content design structure. In another example, a method adapts the original content design structure when translated content is inconsistent with the original content design structure. In yet another example, an image analysis method is used to adapt translated content determined to be inconsistent with the original content design structure.

FIELD

The field relates generally to information processing systems, and moreparticularly to techniques for localization of content presentations insuch information processing systems.

BACKGROUND

Content localization is typically considered the process of adapting anexisting content presentation to a local language and, if possible,culture in a target market. By way of example, website localizationadapts one or more web pages of an existing website to the locallanguage and culture in a specific target market. Localization caninvolve more than the translation of text. Localization can reflectspecific language and cultural preferences in images, overall design andrequirements of the website, all while maintaining the integrity of thewebsite.

A culturally adapted web site will make navigation easier for the users,and thus their attitude towards the site will be much more positive.Furthermore, a main purpose of localization is to customize a website ina way that seems natural to its viewers, despite certain culturaldifferences between the creator and the audience. As people speakdifferent languages, worldwide website localization has become one ofthe primary tools for global business expansion. It is clear thatlinguistic and cultural knowledge is essential for this purpose, butprogramming expertise is also necessary.

SUMMARY

Embodiments of the invention provide techniques for localization of acontent presentation in an information processing system. For example,in one illustrative embodiment, a method adapts translated content toaccommodate an original content design structure (e.g., wireframe) whensuch translated content is inconsistent with the original content designstructure. In another illustrative embodiment, a method adapts theoriginal content design structure when translated content isinconsistent with the original content design structure. In yet anotherillustrative embodiment, an image analysis method is used to adapttranslated content determined to be inconsistent with the originalcontent design structure.

Advantageously, illustrative embodiments provide, inter alia, aconsistent user experience in all global languages, a reduced cost oftesting pages, and accelerated web development due to reduction ofmultiple design updates to the wireframes.

These and other features and advantages of the invention will becomemore readily apparent from the accompanying drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example of a content design structure with which oneor more illustrative embodiments can be implemented.

FIG. 2 depicts an example of truncated content after content translationof a webpage.

FIG. 3 depicts an example of misaligned content after contenttranslation of a webpage.

FIG. 4 depicts an information processing system with contentpresentation localization, according to an illustrative embodiment.

FIG. 5 depicts a content adaptation methodology for content presentationlocalization, according to an illustrative embodiment.

FIG. 6 depicts a content design structure adaptation methodology forcontent presentation localization, according to an illustrativeembodiment.

FIG. 7 depicts an image analysis-based adaptation methodology forcontent presentation localization, according to an illustrativeembodiment.

FIG. 8 depicts a processing platform used to implement an informationprocessing system with content presentation localization, according toan illustrative embodiment.

DETAILED DESCRIPTION

Illustrative embodiments will be described herein with reference toexemplary information processing systems and associated host devices,storage devices and other processing devices. It is to be appreciated,however, that embodiments are not necessarily restricted to use with theparticular illustrative system and device configurations shown.Accordingly, the term “information processing system” as used herein isintended to be broadly construed, so as to encompass, for example,processing systems comprising cloud computing and storage systems, aswell as other types of processing systems comprising variouscombinations of physical and virtual computing resources. An informationprocessing system may therefore comprise, for example, a cloudinfrastructure hosting multiple tenants that share cloud computingresources. Such systems are considered examples of what are moregenerally referred to herein as cloud computing environments.

Furthermore, some cloud infrastructures are within the exclusive controland management of a given enterprise, and therefore are considered“private clouds.” The term “enterprise” as used herein is intended to bebroadly construed, and may comprise, for example, one or morebusinesses, one or more corporations or any other one or more entities,groups, or organizations. An “entity” as illustratively used herein maybe a person or a computing system. On the other hand, cloudinfrastructures that are used by multiple enterprises, and notnecessarily controlled or managed by any of the multiple enterprises butrather are respectively controlled and managed by third-party cloudproviders, are typically considered “public clouds.” Thus, enterprisescan choose to host their applications or services on private clouds,public clouds, and/or a combination of private and public clouds (hybridcloud computing environment). A computing environment that comprisesmultiple cloud platforms (private clouds, public clouds, or acombination thereof) is referred to as a “multi-cloud computingenvironment.”

Still further, an information processing system may comprise non-cloudinfrastructure, or a combination of non-cloud and cloud infrastructures.Moreover, phrases such as “computing environment,” “cloud environment,”“cloud computing platform,” “cloud infrastructure,” “data repository,”“data center,” “data processing system,” “computing system,” “datastorage system,” “information processing system,” and the like, as usedherein, are intended to be broadly construed, so as to encompass, forexample, any arrangement of one or more processing devices.

While examples of content presentations described herein focus onwebpages, it is to be appreciated that embodiments are intended to applyto localization of any suitable electronic content presentationsincluding, but not limited to, presentation of data pages, data files,data templates, data objects, articles, billboards, and the like.

Furthermore, illustrative embodiments realize that the importance ofdesign plays a critical role in localizing any website because aflexible design enables pages to scale based on dynamic content.Compared to English for instance, some languages have words that aresignificantly longer or significantly shorter. For instance, most of theAsian languages contain words that could be less than half the sourcelanguage width. Illustrative embodiments provide techniques for contentpresentation localization that account for these and other challenges.

Prior to describing illustrative embodiments, the concept of wireframingof web pages is briefly described along with some drawbacks associatedwith existing webpage content localization techniques.

Referring initially to FIG. 1, an example of a wireframe 100 associatedwith a webpage design is shown. Wireframing is a way to design a websiteat the structural level. A wireframe is commonly used to lay out contentand functionality on a page which takes into account, for example, userneeds and user goals. Wireframes are used early in the developmentprocess to establish the basic structure of a page before visual designand content is added. One of the great advantages of wireframing is thatit provides an early visual that can be used to review with the client.Users can also review it as an early feedback mechanism for prototypeusability tests. Not only are wireframes easier to amend than conceptdesigns, once approved by the client and the users they provideconfidence to the designer. However, when content is added, it mightinitially be too much to fit within the wireframe layout, so thedesigner and copywriter will need to work closely to make this fit.

When a page is not localized with factoring design limitations andrequirements, the page when translated into a different language showsbroken text such as in the example webpage 200 in FIG. 2. Moreparticularly, as highlighted by box 202 in FIG. 2, the translated textappears truncated. FIG. 3 is another example webpage 300 where thewireframe alignment is broken when an English site is translated intoPortuguese. More particularly, as highlighted by box 302 in FIG. 3, thealignment of the translated text is not proper.

Maintaining design flexibility is a challenging task as it requirestesting in different languages and readjusting multiple times. One ormore illustrative embodiments provide techniques to reframe wireframes,or more generally, content design structures, that support any languageby enabling an automatic choice of flexible linguistic options whilemaintaining the original user accepted wireframes. In alternativeembodiments, the translated content is not adapted but rather theoriginal wireframe is adapted in an optimal way to accommodate thetranslated content.

FIG. 4 depicts an information processing system 400 with contentpresentation localization, according to an illustrative embodiment. Asshown, content presentation localization system 410 comprises a set ofprocessing engines that provide various localization features withrespect to a content design structure such as, but not limited to, awireframe. More particularly, content presentation localization system410 comprises a content adaptation engine 412, a content designstructure adaptation engine 414, an image analysis-based adaptationengine 416, supported translation languages 417 and a contentpresentation selector 418 operatively coupled to one another. It is tobe appreciated that each of engines 412, 414 and 416 can provide astand-alone localization feature for a user. However, two or more of thelocalization features can be combined to provide further advantages. Asshown, various inputs are provided to the content presentationlocalization system 410 depending on the particular processing engine(412, 414, 416), e.g., content in original language 420 and contentdesign structure requirements 422. The output of the contentpresentation localization system 410 is localized content 430, i.e.,content 420 is adapting to a local language and culture in a targetmarket to yield localized content 430. That is, based on analysis outputand/or recommendation(s) generated by one or more of content adaptationengine 412, content design structure adaptation engine 414 and imageanalysis-based adaptation engine 416, content presentation selector 418selects the localized content 430, i.e., the content 420 adapted to alocal language (of the supported translation languages 417) and culturewithin a wireframe structure that eliminates or at least minimizespresentation issues such as, but not limited to, truncation (e.g.,recall FIG. 2) and misalignment (e.g., recall FIG. 3). In other words,selector 418 is configured to select which adapted presentation from themultiple engines is presented as the localized content 430. The criteriafor selection may be predetermined by a content manager and/orautomatically determined by an artificial intelligence (AI)/machinelearning (ML) system. Alternatively, in embodiments where system 410 isconfigured with just one of engine 412, 414 or 416, selector 418 is notneeded. Localized content, in illustrative embodiments, may be in theform of one or more web pages. Thus, in illustrative embodiments, a webpage can be considered content added to a wireframe. The supportedtranslation languages 417 may be one or more languages predetermined byoperators of the system 410. System 410 can be updated with differenttranslation languages as the need/desire arises.

As will be further explained in detail below in the context of FIG. 5,content adaptation engine 412 inputs content design structure (e.g.,wireframe) requirements 422 and the content in the original language420, and finds the best matching translated content for the supportedlanguages 417 that is consistent with the original content designstructure requirements 422, i.e., that does not exhibit presentationissues such as, but not limited to, truncation and misalignment.

More particularly, engine 412 is configured to convert original contentto each destination language and then identify alternativewords/sentences (text having the same or similar meaning) within thetranslated destination language to replace initially-translatedwords/sentences in the translated destination language that cause apresentation problem for the original wireframe. For example, assumethat the original content is in English and the destination language isFrench. After the original content is translated to French, assume thereis one or more truncation/misalignment problems with the wireframe withthe initial French translation. Thus, engine 412 identifies alternativeFrench words/sentences that avoid the truncation/misalignment issues. Itis to be appreciated that system 410 is not limited to any particularoriginal language or any set of destination languages mentioned inexamples herein. In one or more illustrative embodiments, the languagesare decided by one or more content managers driven by their user/readerbase.

Additionally or alternatively, in one illustrative embodiment, engine412 can be configured to convert original content to every languagesupported by the system (or some predetermined subset) and then identifythe translated language that best fits the original wireframe (e.g.,translated words/sentences that best fit into the space limitationsalloted by the original wireframe). For example, assume that theoriginal content is in English and that the system 410 supports Frenchand Arabic as translated destination languages. After the originalcontent is translated to both French and Arabic, assume there is one ormore truncation/misalignment problems with the wireframe with the Frenchtranslation but not the Arabic translation. Thus, engine 412 identifiesArabic as the best language for that given original wireframe design.That is, it can be useful to know for future web page development inArabic that one particular wireframe design is more accomodating to thatlanguage than other wireframe designs.

More particularly, FIG. 5 depicts an illustrative embodiment of amethodology 500 executed by content adaptation engine 412. As shown inmethodology 500, step 502 extracts pre-defined values of scope andboundaries of different user interface (UI) elements of a given originalwireframe design. Examples of such scope and boundaries values mayinclude, but are not limited to, width and height dimensions of a textbox in the original wireframe, width and height dimensions of adrop-down menu, etc. These values are part of the requirements 422 inputto system 410 (see FIG. 4). Step 504 applies the one or more supportedlanguages (1 . . . . n) on the wireframe. For example, the contentadaptation engine 412 translates the original content in the sourcelanguage using machine translation to the one or more supportedlanguages. Step 506 calculates the change in the scope and boundariesvalues for each set of translated content against the scope andboundaries values for each corresponding set of original content. Forexample, recall that in the UI feature in FIG. 2 highlighted as 202, thetext translated into Portuguese would necessitate a change to thedimensions (scope and boundaries values) of the original UI featuredefined for the source language. Step 508 then flags (e.g., marks orotherwise identifies) each component (UI feature) that has atruncation/misalignment issue following translation. For example, inaccordance with one or more illustrative embodiments, when there is adifference that causes such truncation/misalignment, it is said that theUI feature or component is out of scope. Step 510 checks for any flaggedcomponents and if there are none, then methodology 500 ends (512). Moreparticularly, this means that after translation, none of the translatedcontent in the UI features of interest has a truncation/misalignmentissue and, as such, each wireframe translated into a supported languageis approved by engine 412 as language-compliant and can thus be selectedas localized content 430.

However, if step 510 indicates one or more flagged components, then thetranslation language, component (UI feature) and text is flagged in step514 and provided to a natural language processing (NLP) module 520 toselect text in the translated language that can be used in place of theoriginal translated text. As is known, for example, NLP includescomputer science fields of study that focus on artificial intelligence(AI)/machine learning (ML) algorithms that process and analyze naturallanguage data. Module 520 depicts just one example of an NLP processingpipeline that includes sentence segmentation 521, tokenization 522,lemmatization 523, stop words filtering 524, part of speech tagging 525and name entity recognition 526. Each of these processes are known tothose of ordinary skill in the art and thus will only be summarilydescribed. Sentence segmentation 521 finds the sentence boundaries(e.g., periods or other punctuation marks) for a set of input text.Tokenization 522 breaks up the sentences into tokens (e.g., words,punctuation marks, etc.). Lemmatization 523 removes inflectional endingsand returns the base dictionary form of a word (known as a “lemma”).Stop word filtering 524 identifies words that are considered commonwords, function words, very short words, etc. in a given language andremoves/excludes them from the given text so that greater focus is givento those words which define the meaning of the text. Part of speechtagging 525 determines the part of speech (e.g., noun, verb, etc.) foreach word. Name entity recognition 526 determines which words are propernames, such as people or places, and what the type of each such name is(e.g., person, location, organization, etc.).

From the NLP processing pipeline of steps 521 through 526, step 527selects optimal text that eliminates and/or minimizes anytruncation/misalignment issue that led to the component being flagged.Once the alternative text is selected via NLP module 520, steps 506through 514 are repeated, and the component/text with wireframe will nowbe language-compliant. However, if there are any remaining flaggedcomponent/text for a given translated language, they can be processed byNLP module 520 as mentioned above to yield compliant wireframes in eachsupported language.

Turning now to content design structure adaptation engine 414, engine414 determines the optimal content design structure (e.g., wireframe)that supports the translated text that requires minimal changes tooriginal design requirements. Thus, while content adaptation engine 412keeps the original wireframe design constant and finds the optimal textto include in the translated wireframe, engine 414 keeps the textconstant and optimally adapts the original wireframe design. Moreparticularly, content adaptation engine 412 finds the best text byrecommending changes in the words/sentences in the supported languagesby maintaining a constant (unadapted) content design structure, whilecontent design structure adaptation engine 414 finds the best design byrecommending changes in the wireframe or arrangements of componentswhile maintaining words/sentences as constant (unadapted) in thesupported languages.

More particularly, content design structure adaptation engine 414 firstanalyzes the scope and boundaries values (see description above in thecontext of FIG. 5) of the different components in the original wireframestructure. Engine 416 converts the original text/sentences (content 420)into the different supported languages 417 and lists the componentswhere the converted text is out of scope/inconsistent, e.g., hastruncation/misalignment issues. For all such components, engine 416determines the optimal dimension (e.g., maximum length) that is neededby the truncated/misaligned text, and adapts the wireframe by changingthe dimension accordingly, i.e., to properly accommodate the translatedtext. In some cases, some dimensions may proportionally decrease fromadjacent components, and supported languages can be re-checked on theadjacent components that are downsized.

More particularly, FIG. 6 depicts an illustrative embodiment of amethodology 600 executed by content design structure adaptation engine414. As shown in methodology 600, step 602 extracts pre-defined valuesof scope and boundaries of different UI elements of a given originalwireframe design. As mentioned above, examples of such scope andboundaries may include, but are not limited to, width and lengthdimensions of a text box in the original wireframe, width and lengthdimensions of a drop-down menu, etc. Again, these values are part of therequirements 422 input to system 410 (see FIG. 4). Step 604 applies eachof the one or more supported languages (1 . . . . n) on the wireframe.For example, the content design structure adaptation engine 414translates the original content in the source language using machinetranslation to each of the one or more supported languages. Note thatstep 614 iterates the translation process for each supported languageusing the variable n. Step 606 then extracts values of scope andboundaries of different UI elements after applying the given supportinglanguage.

Step 608 checks whether any difference is found between the scope andboundary values of the original wireframe for the source content ascompared with the translated content. If yes, step 610 then flags (e.g.,marks or otherwise identifies) each component (UI feature) for whichtext has moved beyond the component predefined dimensions (e.g., atruncation/misalignment issue following translation). Step 612 increasesvariable m (flag count) by 1 and decreases n by 1. If n is greater than1 in step 614, meaning that there are still one or more remainingsupported languages to be applied, then steps 604 through 612 arerepeated for each remaining supporting language. Step 616 tracks theflag count m. Thus, flag count m tracks the number of out of scopecomponents following translation of content into each of the supportedlanguages. Step 618 determines (e.g., extracts out) the maximum lengthneeded for a given flagged component with respect to each of thelanguages. Step 620 upsizes the flagged component to the maximum lengthneeded to accommodate all the translations, while step 622 downsizes anyadjacent components as needed with equal proportion. Once the originalwireframe is adapted for each translation, in step 624, each adaptedwireframe with translated content is considered language-compliant.

Turning now to image analysis-based adaptation engine 416, engine 416 isconfigured to find the optimal text (by recommending changes in thesentence/words) in all supported languages for a constant wireframedesign. While engine 416 can function as a standalone adaptation featurefor localization of a content presentation, in some embodiments, imageanalysis in engine 416 can be used as a supplemental way to compare(iteratively or otherwise) wireframes with translated content againstthe original wireframe designs after results from engine 412 and/orengine 414 without human intervention. In some embodiments, the imageanalysis can employ artificial intelligence (AI)/machine language (ML)algorithms to do the comparisons.

More particularly, FIG. 7 depicts an illustrative embodiment of amethodology 700 executed by image analysis-based adaptation engine 416.As shown in methodology 700, step 702 applies each of the one or moresupported languages (1 . . . . n) on the original wireframe. Forexample, engine 416 translates the original content in the sourcelanguage using machine translation to each of the one or more supportedlanguages. In step 704, a snapshot (image) of each wireframe withtranslated content is taken (e.g., a web page screenshot is extracted)and each image is compared with a snapshot of the original wireframewith content (previously captured or captured in step 704). Using imagerecognition (e.g., computer vision algorithm, visual object comparison),step 706 cross-validates the wireframes with translated content againstthe original wireframe with content. In step 708, engine 416 finds thediversion in corresponding UI elements between the original wireframeand each translation wireframe. For example, step 708 flags any imageswhere translated text overflows the original wireframe dimensions. Step710 maintains a flag count and for each flagged image, and the languageof the translated content is flagged in step 712. Step 714 identifiesand fetches a synonym (or text with like meaning) of the overflowingtext in the translated language that does not presenttruncation/misalignment issues. Step 716 then applies the synonym to thewireframe, i.e., the initially-translated text is replaced with itssynonym in that particular translation language. Additionally oralternatively, once the image of the translated content is flagged, thewireframe as opposed to the content can be modified as explained abovein the context of FIG. 6.

Furthermore, one or more of engines 412, 414 and 416 can use abag-of-words representation to process the content during engineoperations. The term “bag-of-words” or “bag-of-words model”illustratively refers to a simplified representation of a givenelectronic text (e.g., article, paper, etc.) used in natural languageprocessing and/or information retrieval. In a bag-of-words model, a textis represented as a “bag” of its individual words, disregarding grammarand word order, and the model measures and indicates word multiplicity(i.e., a measure of the occurrence of words in the text).

While content localization is described above in illustrativeembodiments with respect to text, it is to be appreciated thatalternative embodiments can adapt images, designs and other features ofa web site, all while maintaining the integrity of the web site.

FIG. 8 depicts a processing platform 800 used to implement aninformation processing system configured to provide localization of acontent presentation, according to an illustrative embodiment. Moreparticularly, processing platform 800 is a processing platform on whicha computing environment with functionalities described herein (e.g.,FIGS. 1-7 and otherwise described herein) can be implemented.

The processing platform 800 in this embodiment comprises a plurality ofprocessing devices, denoted 802-1, 802-2, 802-3, . . . 802-N, whichcommunicate with one another over network(s) 804. It is to beappreciated that the methodologies described herein may be executed inone such processing device 802, or executed in a distributed manneracross two or more such processing devices 802. It is to be furtherappreciated that a server, a client device, a computing device or anyother processing platform element may be viewed as an example of what ismore generally referred to herein as a “processing device.” Asillustrated in FIG. 8, such a device generally comprises at least oneprocessor and an associated memory, and implements one or morefunctional modules for instantiating and/or controlling features ofsystems and methodologies described herein. Multiple elements or modulesmay be implemented by a single processing device in a given embodiment.Note that components described in the architectures depicted in thefigures can comprise one or more of such processing devices 802 shown inFIG. 8. The network(s) 804 represent one or more communications networksthat enable components to communicate and to transfer data therebetween,as well as to perform other functionalities described herein.

The processing device 802-1 in the processing platform 800 comprises aprocessor 810 coupled to a memory 812. The processor 810 may comprise amicroprocessor, a microcontroller, an application-specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or other type ofprocessing circuitry, as well as portions or combinations of suchcircuitry elements. Components of systems as disclosed herein can beimplemented at least in part in the form of one or more softwareprograms stored in memory and executed by a processor of a processingdevice such as processor 810. Memory 812 (or other storage device)having such program code embodied therein is an example of what is moregenerally referred to herein as a processor-readable storage medium.Articles of manufacture comprising such processor-readable storage mediaare considered embodiments of the invention. A given such article ofmanufacture may comprise, for example, a storage device such as astorage disk, a storage array or an integrated circuit containingmemory. The term “article of manufacture” as used herein should beunderstood to exclude transitory, propagating signals.

Furthermore, memory 812 may comprise electronic memory such asrandom-access memory (RAM), read-only memory (ROM) or other types ofmemory, in any combination. The one or more software programs whenexecuted by a processing device such as the processing device 802-1causes the device to perform functions associated with one or more ofthe components/steps of system/methodologies in FIGS. 1-7. One skilledin the art would be readily able to implement such software given theteachings provided herein. Other examples of processor-readable storagemedia embodying embodiments of the invention may include, for example,optical or magnetic disks.

Processing device 802-1 also includes network interface circuitry 814,which is used to interface the device with the networks 804 and othersystem components. Such circuitry may comprise conventional transceiversof a type well known in the art.

The other processing devices 802 (802-2, 802-3, . . . 802-N) of theprocessing platform 800 are assumed to be configured in a manner similarto that shown for computing device 802-1 in the figure.

The processing platform 800 shown in FIG. 8 may comprise additionalknown components such as batch processing systems, parallel processingsystems, physical machines, virtual machines, virtual switches, storagevolumes, etc. Again, the particular processing platform shown in thisfigure is presented by way of example only, and the system shown as 800in FIG. 8 may include additional or alternative processing platforms, aswell as numerous distinct processing platforms in any combination.

Also, numerous other arrangements of servers, clients, computers,storage devices or other components are possible in processing platform800. Such components can communicate with other elements of theprocessing platform 800 over any type of network, such as a wide areanetwork (WAN), a local area network (LAN), a satellite network, atelephone or cable network, or various portions or combinations of theseand other types of networks.

Furthermore, it is to be appreciated that the processing platform 800 ofFIG. 8 can comprise virtual (logical) processing elements implementedusing a hypervisor. A hypervisor is an example of what is more generallyreferred to herein as “virtualization infrastructure.” The hypervisorruns on physical infrastructure. As such, the techniques illustrativelydescribed herein can be provided in accordance with one or more cloudservices. The cloud services thus run on respective ones of the virtualmachines under the control of the hypervisor. Processing platform 800may also include multiple hypervisors, each running on its own physicalinfrastructure. Portions of that physical infrastructure might bevirtualized.

As is known, virtual machines are logical processing elements that maybe instantiated on one or more physical processing elements (e.g.,servers, computers, processing devices). That is, a “virtual machine”generally refers to a software implementation of a machine (i.e., acomputer) that executes programs like a physical machine. Thus,different virtual machines can run different operating systems andmultiple applications on the same physical computer. Virtualization isimplemented by the hypervisor which is directly inserted on top of thecomputer hardware in order to allocate hardware resources of thephysical computer dynamically and transparently. The hypervisor affordsthe ability for multiple operating systems to run concurrently on asingle physical computer and share hardware resources with each other.

It was noted above that portions of the computing environment may beimplemented using one or more processing platforms. A given suchprocessing platform comprises at least one processing device comprisinga processor coupled to a memory, and the processing device may beimplemented at least in part utilizing one or more virtual machines,containers or other virtualization infrastructure. By way of example,such containers may be Docker containers or other types of containers.As illustratively used herein, a container is considered a “virtualcomputing element” (e.g., unit of software) that packages applicationcode and its dependencies so that the application is executed quicklyand reliably from one computing environment to another. A Dockercontainer image is a lightweight, standalone, executable package ofsoftware that includes all components needed to execute an application.

The particular processing operations and other system functionalitydescribed in conjunction with FIGS. 1-8 are presented by way ofillustrative example only, and should not be construed as limiting thescope of the disclosure in any way. Alternative embodiments can useother types of operations and protocols. For example, the ordering ofthe steps may be varied in other embodiments, or certain steps may beperformed at least in part concurrently with one another rather thanserially. Also, one or more of the steps may be repeated periodically,or multiple instances of the methods can be performed in parallel withone another.

It should again be emphasized that the above-described embodiments ofthe invention are presented for purposes of illustration only. Manyvariations may be made in the particular arrangements shown. Forexample, although described in the context of particular system anddevice configurations, the techniques are applicable to a wide varietyof other types of data processing systems, processing devices anddistributed virtual infrastructure arrangements. In addition, anysimplifying assumptions made above in the course of describing theillustrative embodiments should also be viewed as exemplary rather thanas requirements or limitations of the invention. Numerous otheralternative embodiments within the scope of the appended claims will bereadily apparent to those skilled in the art.

What is claimed is:
 1. A system, comprising: at least one processingdevice comprising a processor operatively coupled to a memory, whereinthe at least one processing device, for a given content presentation, isconfigured to: obtain content in a source language and a content designstructure that is consistent with the source language content; translatethe source language content to content in at least one destinationlanguage; evaluate the translated content for one or moreinconsistencies with respect to the content design structure; and adaptone or more inconsistent portions of translated content to generate oneor more adapted portions of translated content that are consistent withthe content design structure such that the given content presentation islocalized for the at least one destination language.
 2. The system ofclaim 1, wherein evaluating the translated content for one or moreinconsistencies with respect to the content design structure furthercomprises determining one or more dimensions associated with componentsof the content design structure for which a portion of the translatedcontent is out of scope.
 3. The system of claim 2, wherein a portion oftranslated content is out of scope when the portion of translatedcontent is one of truncated and misaligned in the content designstructure as compared with the corresponding portion of source languagecontent.
 4. The system of claim 1, wherein adapting one or moreinconsistent portions of translated content to generate one or moreadapted portions of translated content that are consistent with thecontent design structure further comprises obtaining one or moreportions of alternative translated content that have a same or similarmeaning to the one or more inconsistent portions of translated contentand that are consistent with one or more dimensions associated withcorresponding components of the content design structure.
 5. The systemof claim 4, wherein obtaining one or more portions of alternativetranslated content that have a same or similar meaning to the one ormore inconsistent portions of translated content and that are consistentwith one or more dimensions associated with corresponding components ofthe content design structure further comprises using a natural languageprocessing pipeline.
 6. The system of claim 1, wherein the systemsupports multiple destination languages, the at least one processingdevice being further configured to determine a destination language fromthe multiple destination languages that is most consistent with thecontent design structure.
 7. The system of claim 1, wherein the contentpresentation localized for the at least one destination language is atleast one web page.
 8. The system of claim 1, wherein the content in thesource language comprises one or more of text, an image and a designelement.
 9. A method, comprising: obtaining, for a given contentpresentation, content in a source language and a content designstructure that is consistent with the source language content;translating the source language content to content in at least onedestination language; evaluating the translated content for one or moreinconsistencies with respect to the content design structure; andadapting one or more inconsistent portions of translated content togenerate one or more adapted portions of translated content that areconsistent with the content design structure such that the contentpresentation is localized for the at least one destination language;wherein the steps are performed by at least one processing devicecomprising a processor operatively coupled to a memory.
 10. The methodof claim 9, wherein evaluating the translated content for one or moreinconsistencies with respect to the content design structure furthercomprises determining one or more dimensions associated with componentsof the content design structure for which a portion of the translatedcontent is out of scope.
 11. The method of claim 10, wherein a portionof translated content is out of scope when the portion of translatedcontent is one of truncated and misaligned in the content designstructure as compared with the corresponding portion of source languagecontent.
 12. The method of claim 9, wherein adapting one or moreinconsistent portions of translated content to generate one or moreadapted portions of translated content that are consistent with thecontent design structure further comprises obtaining one or moreportions of alternative translated content that have a same or similarmeaning to the one or more inconsistent portions of translated contentand that are consistent with one or more dimensions associated withcorresponding components of the content design structure.
 13. The methodof claim 12, wherein obtaining one or more portions of alternativetranslated content that have a same or similar meaning to the one ormore inconsistent portions of translated content and that are consistentwith one or more dimensions associated with corresponding components ofthe content design structure further comprises using a natural languageprocessing pipeline.
 14. The method of claim 9, wherein the systemsupports multiple destination languages, further comprising determininga destination language from the multiple destination languages that ismost consistent with the content design structure.
 15. The method ofclaim 9, wherein the content presentation localized for the at least onedestination language is at least one web page.
 16. The method of claim9, wherein the content in the source language comprises one or more oftext, an image and a design element.
 17. An article of manufacturecomprising a non-transitory processor-readable storage medium havingstored therein program code of one or more software programs, whereinthe program code when executed by at least one processing device causessaid at least one processing device to perform steps of: obtaining, fora given content presentation, content in a source language and a contentdesign structure that is consistent with the source language content;translating the source language content to content in at least onedestination language; evaluating the translated content for one or moreinconsistencies with respect to the content design structure; andadapting one or more inconsistent portions of translated content togenerate one or more adapted portions of translated content that areconsistent with the content design structure such that the given contentpresentation is localized for the at least one destination language. 18.The article of claim 17, wherein evaluating the translated content forone or more inconsistencies with respect to the content design structurefurther comprises determining one or more dimensions associated withcomponents of the content design structure for which a portion of thetranslated content is out of scope.
 19. The article of claim 18, whereina portion of translated content is out of scope when the portion oftranslated content is one of truncated and misaligned in the contentdesign structure as compared with the corresponding portion of sourcelanguage content.
 20. The article of claim 17, wherein adapting one ormore inconsistent portions of translated content to generate one or moreadapted portions of translated content that are consistent with thecontent design structure further comprises obtaining one or moreportions of alternative translated content that have a same or similarmeaning to the one or more inconsistent portions of translated contentand that are consistent with one or more dimensions associated withcorresponding components of the content design structure.